In recent years, with increases in the variety, image quality, accuracy, and the like of information, the amount of data included in one piece of information has increased. There has also increased a demand to process an extremely large amount of data called big data when controlling social infrastructure or analyzing natural phenomena or the like. Accordingly, storage systems for storing such a great amount of data are increasing their importance. When selecting such a storage system, greater importance is placed on its performance and capacity, as well as on its reliability.
What is important with respect to the reliability of a storage system is to prevent an error from occurring in data stored in a storage device such as a disk, as well as to prevent a fault from causing an error in data being transferred within a storage system. Even when data can be correctly read from a disk or the like, if a fault occurs and causes an error in data being transferred within the storage system before outputted therefrom, a process using such data would malfunction, causing a significant problem.
What is also important with respect to the reliability of a storage system is to identify the faulty portion in the storage system. If the entire storage system is shut down due to a fault in part thereof and thus read or write of data therefrom or thereto becomes impossible, the process using the data is delayed, significantly affecting use of the storage system.
For example, PTL1 discloses a technology which quickly calculates an error correction code (ECC), which is also used to detect an error in data, by using hardware in place of software, which has been used traditionally.